Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Objective To investigate the pharmacological mechanism through which total flavonoids extracted from Xiaobuxin-Tang(XBXT-2)affects neural network activities in the frontal cortex by focusing on the effects of XBXT-2 on the cortical field potentials in the frontal association cortex(FrA)in mice.Methods Cortical electrodes were implanted into the skull of C57BL/6J mice targeting the FrA.After a 7-day recovery period,the mice were administered XBXT-2 intragastrically at a dose of 100 mg/kg,and 1 hour later,local field potential(LFP)in the FrA were recorded for 30 minutes.Spectral analysis of the data was performed using Neuro Explorer software.Changes in the power spectral density of α,β,θ,γ,and δ frequency bands before and after drug administration were analyzed using GraphPad Prism 10.3.Phase-amplitude coupling of θ and γ oscillations was analyzed using Matlab 2021 software.Results It was found that the oral administration of XBXT-2 significantly suppressed high-frequency γ oscillations while simultaneously enhancing θ,β,α,and δ oscillations in FrA of mice compared to the control.Furthermore,XBXT-2 treatment markedly strengthened the phase-amplitude coupling between θ and γ oscillations.Conclusion XBXT-2 possibly affects emotional and cognitive functions by modulating neural network activity in FrA and enhancing θ-γ phase-amplitude coupling in mice.

Objective To analyze the clinical characteristics,treatment and prognosis of patients undergoing the maintenance hemodialysis and treatment-naive tuberculosis and to explore the prognostic factors,so as to provide a reference for the clinical treatment of patients undergoing hemodialysis due to tuberculosis.Methods The clinical data of 70 patients undergoing hemodialysis with treatment-naive tuberculosis admitted to the Third People's Hospital of Kunming from October 31,2020～October 31,2023 were retrospectively collected,the clinical characteristics of the patients were analyzed,and the occurrence of adverse reactions,treatment outcomes and prognostic factors were observed.Results Among the 70 patients,pulmonary tuberculosis was the primary type(64 cases,accounting for 91.43％),and extrapulmonary tuberculosis was also quite common(56 cases,accounting for 80.00％).The most widely used anti-tuberculosis regimen was isoniazid,rifampicin,ethambutol,and moxifloxacin in a four-drug combination;During the anti-tuberculosis treatment,55 patients(78.57％)improved.A total of 13 adverse reactions occurred in 11 patients(15.71％),and the most common ones were itching,rash and blurred vision.The hemoglobin,lymphocyte count and CD8+T lymphocyte count in the treatment improvement group were higher than those in the ineffective group(P<0.05).Conclusion Dialysis patients have a high risk of tuberculosis infection,mainly pulmonary tuberculosis,and extrapulmonary tuberculosis is more common.78.57％of the patients hare improved after the tuberculosis treatment,but the overall prognosis is poor,and the low hemoglobin level is associated with ineffective treatment.

Objective To analyze the efficacy of different nucleoside(acid)analogs(NAs)used as monotherapy and in combination with pegylated interferon α-2b(Peg-IFN-α-2b)in the treatment of chronic hepatitis B(CHB).Methods A retrospective analysis was conducted on 229 CHB patients who visited the Hepatology Department of the Third People's Hospital of Kunming from September 2022 to August 2023.Patients were divided into six groups based on their antiviral regimen:entecavir(ETV)group(A,n=47),ETV combined with Peg-IFN-α-2b group(B,n=19),Tenofovir Alafenamide(TMF)group(C,n=64),TMF combined with Peg-IFN-α-2b group(D,n=35),Tenofovir Disoproxil Fumarate(TDF)group(E,n=29),and TDF combined with Peg-IFN-α-2b group(F,n=35).The blood routine,liver function,kidney function,HBV serological markers,and HBV-DNA levels were compared before and after 24 weeks of treatment.Results After 24 weeks of treatment,there were no statistically significant differences in efficacy rates and HBV-DNA positivity rates between the monotherapy with NAs and the combination with Peg-IFN-α-2b(P>0.05).Comparing before and after treatment,the ETV group had the highest effective rate,while TDF combined with Peg-IFN-α-2b group had the lowest effective rate.TDF group had the highest efficiency,while ETV combined with Peg-IFN-α-2b group had the lowest efficiency.Except for ETV+Peg-IFN-α-2b and TDF+Peg-IFN-α-2b groups,the HBV-DNA positivity rates in the other four groups were significantly lower after treatment compared to before(P<0.05).There was a significant difference in HBsAg levels among the different treatment regimens of monotherapy with NAs and combination with Peg-IFN-α-2b(P=0.0483).Additionally,except for the ETV and TDF groups,the serum HBsAg levels in the other four groups were significantly lower after treatment compared to before(P<0.05).There were no significant difference in LSM and GFR before and after treatment(P>0.05).In the monotherapy groups,ALT and GGT levels were significantly lower after treatment compared to before(P<0.05),while in the combination Peg-IFN-α-2b group,WBC,NEUT,and PLT levels were significantly lower after treatment compared to before(P<0.05).Conclusion Combination therapy with Peg-IFN-α-2b can reduce HBsAg levels and may be more effective in controlling the virus;however,it may cause adverse reactions such as bone marrow suppression,increasing risks.Physicians and patients need to weigh the benefits against the risks and develop personalized treatment plans based on individual circumstances.

With the rapid development of artificial intelligence, computational pathology has been seamlessly integrated into the entire clinical workflow, which encompasses diagnosis, treatment, prognosis, and biomarker discovery. This integration has significantly enhanced clinical accuracy and efficiency while reducing the workload for clinicians. Traditionally, research in this field has depended on the collection and labeling of large datasets for specific tasks, followed by the development of task-specific computational pathology models. However, this approach is labor intensive and does not scale efficiently for open-set identification or rare diseases. Given the diversity of clinical tasks, training individual models from scratch to address the whole spectrum of clinical tasks in the pathology workflow is impractical, which highlights the urgent need to transition from task-specific models to foundation models (FMs). In recent years, pathological FMs have proliferated. These FMs can be classified into three categories, namely, pathology image FMs, pathology image-text FMs, and pathology image-gene FMs, each of which results in distinct functionalities and application scenarios. This review provides an overview of the latest research advancements in pathological FMs, with a particular emphasis on their applications in oncology. The key challenges and opportunities presented by pathological FMs in precision oncology are also explored.
Humans ; Precision Medicine/methods* ; Medical Oncology/methods* ; Artificial Intelligence ; Neoplasms/pathology* ; Computational Biology/methods*

Objective To analyze the levels of serum CTCs and ctDNA in NSCLC patients receiving first-line EGFR-TKI treatment, and to explore the clinical value of CTCs and ctDNA detection in assessing the efficacy of treatment for advanced lung cancer. Methods A total of 109 NSCLC patients receiving first-line EGFR-TKI treatment were enrolled. Serum tumor markers CEA, CTCs, and ctDNA were detected at baseline and after one month of treatment. Chest CT scans were performed, and treatment efficacy was evaluated based on RECIST1.1 criteria. CTCs were counted by enrichment-staining-computational algorithm to analyze malignant features, while ctDNA was assessed using digital PCR. Results Survival rate was low in patients with abnormal CEA and ctDNA tests at baseline and in patients with reduced serum CTCs after treatment. In the SD subgroup of patients with brain metastases and advanced stage, the PFS benefit was low. Conclusion Patients in the SD subgroup have significantly higher recurrence risks than those in the PR or CR subgroups. Therefore, CTC and ctDNA testing should be applied to patients in the SD subgroup to identify high-risk patients with poor response to EGFR-TKI treatment, intervene with additional treatment promptly, and obtain long progression-free survival.

Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Objective: To retrospectively compare the impact of different intraoperative transfusion strategies for platelets and cryoprecipitate on perioperative blood usage and clinical outcomes in patients undergoing orthotopic heart transplant (OHT), thereby providing a reference for perioperative patient blood management. Methods: The clinical data of 65 patients who had undergone OHT at our hospital between 2020 and 2025 were retrospective collected. Patient demographics, underlying chronic conditions, and perioperative (preoperative, intraoperative, and postoperative) laboratory blood test results were analyzed. The transfusion volumes of intraoperative red blood cells, plasma, platelets, and cryoprecipitate were examined. Univariate and multivariate logistic regression models were employed to identify factors associated with perioperative outcomes. Results: A total of 65 patients received allogeneic blood transfusion during the perioperative period. The ultilization of intraoperative platelets and cryoprecipitate was as follows: simultaneous transfusion of both platelets and cryoprecipitate (at a 1∶1 ratio) was administered in 42 patients (64.62%), platelets alone in 12 patients (18.46%), and cryoprecipitate alone in 11 patients (16.92%). Patients who received simultaneous transfusion of platelets and cryoprecipitate (1∶1) (n=42) had a shorter ICU length of stay (32.45±10.18 d), while those who received either platelets or cryoprecipitate alone (n=23) had a significantly longer ICU length of stay (68±15.97 d). Patients receiving simultaneous intraoperative transfusion of platelets and cryoprecipitate also required fewer units of allogeneic red blood cells intraoperatively (median=4 units) and had a lower mortality rate (16.7%) than those receiving either product alone (26.1%), with a statistically significant difference (P=0.023). Multivariate logistic regression analysis indicated that the volume of cryoprecipitate transfused was an independent protective factor against postoperative allogeneic red blood cell transfusion (OR=0.344, 95% CI [0.177, 0.829], P=0.0159). Multivariate logistic regression also identified cryoprecipitate transfusion volume as an independent protective factor for ICU length of stay (OR=0.877, 95% CI [0.719, 0.986], P=0.0008), which was in line with the multivariate Cox regression results. Conclusion: In patients undergoing OHT, the intraoperative transfusion strategy for platelets and cryoprecipitate influences the volume of perioperative allogeneic red blood cell transfusion and patient mortality. Intraoperative cryoprecipitate transfusion volume is an independent protective factor against both postoperative allogeneic red blood cell transfusion and prolonged ICU length of stay. The establishment of a multidisciplinary collaborative blood management model, combined with the modification of perioperative blood utilization practices and the implementation of a comprehensive patient blood management strategy, can holistically ensure perioperative patient safety.

Objective: To evaluate the safety and efficacy of the emergency infusion protocol for universal red blood cells by analyzing its clinical application in patients treated at our hospital's war trauma and emergency center. Methods: Data were collected from 133 patients who received universal red blood cell transfusion in the war trauma center of our hospital from January 2016 to December 2024. The basic information, universal red blood cell transfusion volume, compatible blood components, transfusion volume, blood routine (Hb, Hct), liver and kidney function (ALT, AST, TBil, DBil, creatinine, etc.) and coagulation function (PT, APTT, Fib, etc.) before and after transfusion were retrospectively analyzed. Results: Among the 133 patients who received a total of 374 units of universal red blood cells, the 24-hour survival rate was 62.4% (83/133). Spearman correlation analysis showed a positive correlation between shock index and universal red blood cell transfusion volume (r=0.283, P<0.05). Patients were stratified by universal red blood cell transfusion volume (≤ 3 U vs ≥ 4 U). The low volume group had less homotypic red blood cell transfusion volume and total transfusion volume at different time points, and the difference was statistically significant: within 2 h [2(2, 4)vs 4(3, 7), P=0.033<0.05], 0~24 h [6(4, 9) vs 8(6, 14), P=0.028<0.05], total transfusion volume [13(8, 20)vs 19(12, 35), P=0.021<0.05]. No acute hemolytic transfusion reaction occurred within 24 hours after transfusion of universal red blood cell. Conclusion: Universal red blood cells are safe for use in emergency treatment. Furthermore, the shock index combined with the volume of universal red blood cells transfused can predict subsequent transfusion requirements and enables the early reservation of compatible blood, thereby preventing delayed resuscitation.